Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

Results of the MAJORANA DEMONSTRATOR's Search for Double-Beta Decay of 76Ge to Excited States of 76Se

The MAJORANA DEMONSTRATOR is searching for double-beta decay of 76Ge to excited states (E.S.) in 76Se using a modular array of high purity Germanium detectors. 76Ge can decay into three E.S.s of 76Se. The E.S. decays have a clear event signature consisting of a ββ-decay with the prompt emission of one or two γ-rays, resulting in with high probability in a multi-site event. The granularity of the DEMONSTRATOR detector array enables powerful discrimination of this event signature from backgrounds. Using 21.3 kg-y of isotopic exposure, the DEMONSTRATOR has set world leading limits for each E.S. decay, with 90% CL lower half-life limits in the range of (0.56 2.1) ⋅ 1024 y. In particular, for the 2v transition to the first 0+ E.S. of 76Se, a lower half-life limit of 0.68 ⋅ 1024 at 90% CL was achieved

ADC Nonlinearity Correction for the Majorana Demonstrator

Imperfections in analog-to-digital conversion (ADC) cannot be ignored when signal digitization requirements demand both wide dynamic range and high resolution, as is the case for the Majorana Demonstrator 76Ge neutrinoless double-beta decay search. Enabling the experiment's high-resolution spectral analysis and efficient pulse shape discrimination required careful measurement and correction of ADC nonlinearities. A simple measurement protocol was developed that did not require sophisticated equipment or lengthy data-taking campaigns. A slope-dependent hysteresis was observed and characterized. A correction applied to digitized waveforms prior to signal processing reduced the differential and integral nonlinearities by an order of magnitude, eliminating these as dominant contributions to the systematic energy uncertainty at the double-beta decay Q value

Simple model systems: a challenge for Alzheimer's disease

The success of biomedical researches has led to improvement in human health and increased life expectancy. An unexpected consequence has been an increase of age-related diseases and, in particular, neurodegenerative diseases. These disorders are generally late onset and exhibit complex pathologies including memory loss, cognitive defects, movement disorders and death. Here, it is described as the use of simple animal models such as worms, fishes, flies, Ascidians and sea urchins, have facilitated the understanding of several biochemical mechanisms underlying Alzheimer's disease (AD), one of the most diffuse neurodegenerative pathologies. The discovery of specific genes and proteins associated with AD, and the development of new technologies for the production of transgenic animals, has helped researchers to overcome the lack of natural models. Moreover, simple model systems of AD have been utilized to obtain key information for evaluating potential therapeutic interventions and for testing efficacy of putative neuroprotective compounds

The effects of acute CRAM supplementation on reaction time and subjective measures of focus and alertness in healthy college students

<p>Abstract</p> <p>Background</p> <p>The purpose of this study was to examine the effect of acute and prolonged (4-weeks) ingestion of a supplement designed to improve reaction time and subjective measures of alertness, energy, fatigue, and focus compared to placebo.</p> <p>Methods</p> <p>Nineteen physically-active subjects (17 men and 2 women) were randomly assigned to a group that either consumed a supplement (21.1 ± 0.6 years; body mass: 80.6 ± 9.4 kg) or placebo (21.3 ± 0.8 years; body mass: 83.4 ± 18.5 kg). During the initial testing session (T1), subjects were provided 1.5 g of the supplement (CRAM; α-glycerophosphocholine, choline bitartrate, phosphatidylserine, vitamins B3, B6, and B12, folic acid, L-tyrosine, anhydrous caffeine, acetyl-L-carnitine, and naringin) or a placebo (PL), and rested quietly for 10-minutes before completing a questionnaire on subjective feelings of energy, fatigue, alertness and focus (PRE). Subjects then performed a 4-minute quickness and reaction test followed by a 10-min bout of exhaustive exercise. The questionnaire and reaction testing sequence was then repeated (POST). Subjects reported back to the lab (T2) following 4-weeks of supplementation and repeated the testing sequence.</p> <p>Results</p> <p>Reaction time significantly declined (p = 0.050) between PRE and POST at T1 in subjects consuming PL, while subjects under CRAM supplementation were able to maintain (p = 0.114) their performance. Significant performance declines were seen in both groups from PRE to POST at T2. Elevations in fatigue were seen for CRAM at both T1 and T2 (p = 0.001 and p = 0.000, respectively), but only at T2 for PL (p = 0.029). Subjects in CRAM maintained focus between PRE and POST during both T1 and T2 trials (p = 0.152 and p = 0.082, respectively), whereas significant declines in focus were observed between PRE and POST in PL at both trials (p = 0.037 and p = 0.014, respectively). No difference in alertness was seen at T1 between PRE and POST for CRAM (p = 0.083), but a significant decline was recorded at T2 (p = 0.005). Alertness was significantly lower at POST at both T1 and T2 for PL (p = 0.040 and p = 0.33, respectively). No differences in any of these subjective measures were seen between the groups at any time point.</p> <p>Conclusion</p> <p>Results indicate that acute ingestion of CRAM can maintain reaction time, and subjective feelings of focus and alertness to both visual and auditory stimuli in healthy college students following exhaustive exercise. However, some habituation may occur following 4-weeks of supplementation.</p

DNA Methods to Identify Missing Persons

Human identification by DNA analysis in missing person cases typically involves comparison of two categories of sample: a reference sample, which could be obtained from intimate items of the person in question or from family members, and the questioned sample from the unknown person-usually derived from the bones, teeth, or soft tissues of human remains. Exceptions include the analysis of archived tissues, such as those held by hospital pathology departments, and the analysis of samples relating to missing, but living persons. DNA is extracted from the questioned and reference samples and well-characterized regions of the genetic code are amplified from each source using the Polymerase Chain Reaction (PCR), which generates sufficient copies of the target region for visualization and comparison of the genetic sequences obtained from each sample. If the DNA sequences of the questioned and reference samples differ, this is normally sufficient for the questioned DNA to be excluded as having come from the same source. If the sequences are identical, statistical analysis is necessary to determine the probability that the match is a consequence of the questioned sequence coming from the same individual who provided the reference sample or from a randomly occurring individual in the general population. Match probabilities that are currently achievable are frequently greater than 1 in 1 billion, allowing identity to be assigned with considerable confidence in many cases

Effects of Fusion between Tactile and Proprioceptive Inputs on Tactile Perception

Tactile perception is typically considered the result of cortical interpretation of afferent signals from a network of mechanical sensors underneath the skin. Yet, tactile illusion studies suggest that tactile perception can be elicited without afferent signals from mechanoceptors. Therefore, the extent that tactile perception arises from isomorphic mapping of tactile afferents onto the somatosensory cortex remains controversial. We tested whether isomorphic mapping of tactile afferent fibers onto the cortex leads directly to tactile perception by examining whether it is independent from proprioceptive input by evaluating the impact of different hand postures on the perception of a tactile illusion across fingertips. Using the Cutaneous Rabbit Effect, a well studied illusion evoking the perception that a stimulus occurs at a location where none has been delivered, we found that hand posture has a significant effect on the perception of the illusion across the fingertips. This finding emphasizes that tactile perception arises from integration of perceived mechanical and proprioceptive input and not purely from tactile interaction with the external environment

Quantitative trait loci and candidate gene mapping of aluminum tolerance in diploid alfalfa

Aluminum (Al) toxicity in acid soils is a major limitation to the production of alfalfa (Medicago sativa subsp. sativa L.) in the USA. Developing Al-tolerant alfalfa cultivars is one approach to overcome this constraint. Accessions of wild diploid alfalfa (M. sativa subsp. coerulea) have been found to be a source of useful genes for Al tolerance. Previously, two genomic regions associated with Al tolerance were identified in this diploid species using restriction fragment length polymorphism (RFLP) markers and single marker analysis. This study was conducted to identify additional Al-tolerance quantitative trait loci (QTLs); to identify simple sequence repeat (SSR) markers that flank the previously identified QTLs; to map candidate genes associated with Al tolerance from other plant species; and to test for co-localization with mapped QTLs. A genetic linkage map was constructed using EST-SSR markers in a population of 130 BC(1)F(1) plants derived from the cross between Al-sensitive and Al-tolerant genotypes. Three putative QTLs on linkage groups LG I, LG II and LG III, explaining 38, 16 and 27% of the phenotypic variation, respectively, were identified. Six candidate gene markers designed from Medicago truncatula ESTs that showed homology to known Al-tolerance genes identified in other plant species were placed on the QTL map. A marker designed from a candidate gene involved in malic acid release mapped near a marginally significant QTL (LOD 2.83) on LG I. The SSR markers flanking these QTLs will be useful for transferring them to cultivated alfalfa via marker-assisted selection and for pyramiding Al tolerance QTLs

Robot education peers in a situated primary school study: personalisation promotes child learning

The benefit of social robots to support child learning in an educational context over an extended period of time is evaluated. Specifically, the effect of personalisation and adaptation of robot social behaviour is assessed. Two autonomous robots were embedded within two matched classrooms of a primary school for a continuous two week period without experimenter supervision to act as learning companions for the children for familiar and novel subjects. Results suggest that while children in both personalised and non-personalised conditions learned, there was increased child learning of a novel subject exhibited when interacting with a robot that personalised its behaviours, with indications that this benefit extended to other class-based performance. Additional evidence was obtained suggesting that there is increased acceptance of the personalised robot peer over a non-personalised version. These results provide the first evidence in support of peer-robot behavioural personalisation having a positive influence on learning when embedded in a learning environment for an extended period of time